Photosynthesis is a pivotal process in plant physiology, and its regulation plays an important role in plant defense against biotic stress. Interactions with pathogens and pests often cause alterations in the metabolism of sugars and sink/source relationships. These changes can be part of the plant defense mechanisms to limit nutrient availability to the pathogens. In other cases, these alterations can be the result of pests manipulating the plant metabolism for their own benefit. The effects of biotic stress on plant physiology are typically heterogeneous, both spatially and temporarily. Chlorophyll fluorescence imaging is a powerful tool to mine the activity of photosynthesis at cellular, leaf, and whole-plant scale, allowing the phenotyping of plants. This review will recapitulate the responses of the photosynthetic machinery to biotic stress factors, from pathogens (viruses, bacteria, and fungi) to pests (herbivory) analyzed by chlorophyll fluorescence imaging both at the lab and field scale. Moreover, chlorophyll fluorescence imagers and alternative techniques to indirectly evaluate photosynthetic traits used at field scale are also revised.

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Phenotyping Plant Responses to Biotic Stress by Chlorophyll Fluorescence Imaging.

Plant diseases can greatly affect the total production of food and agricultural materials, which may lead to high amount of losses in terms of quality, quantity and also in economic sense. To reduce the losses due to plant diseases, early diseases detection either based on a visual inspection or laboratory tests are widely employed. However, these techniques are labor-intensive and time consuming. In a view to overcome the shortcoming of these conventional approaches, several researchers have developed non-invasive techniques. Recently, spectroscopy technique has become one of the most available non-invasive methods utilized in detecting plant diseases. However, most of the studies on the application of this novel technology are still in the experimental stages, and are carried out in isolation with no comprehensive information on the most suitable approach. This problem could affect the advancement and commercialization of spectroscopy technology in early plant disease detection. Here, we review ...

/pdf/early-detection-of-diseases-in-plant-tissue-using-3stbh0czqj.pdf

Early detection of diseases in plant tissue using spectroscopy – applications and limitations

Huanglongbing (HLB) is one of the most destructive diseases of citrus, which has posed a serious threat to the global citrus production. This research was aimed to explore the use of chlorophyll fluorescence imaging combined with feature selection to characterize and detect the HLB disease. Chlorophyll fluorescence images of citrus leaf samples were measured by an in-house chlorophyll fluorescence imaging system. The commonly used chlorophyll fluorescence parameters provided the first screening of HLB disease. To further explore the photosynthetic fingerprint of HLB infected leaves, three feature selection methods combined with the supervised classifiers were employed to identify the unique fluorescence signature of HLB and perform the three-class classification (i.e., healthy, HLB infected, and nutrient deficient leaves). Unlike the commonly used fluorescence parameters, this novel data-driven approach by using the combination of the mean fluorescence parameters and image features gave the best classification performance with the accuracy of 97%, and presented a better interpretation for the spatial heterogeneity of photochemical and non-photochemical components in HLB infected citrus leaves. These results imply the potential of the proposed approach for the citrus HLB disease diagnosis, and also provide a valuable insight for the photosynthetic response to the HLB disease.

/pdf/chlorophyll-fluorescence-imaging-uncovers-photosynthetic-yhiey0pfzp.pdf

Chlorophyll Fluorescence Imaging Uncovers Photosynthetic Fingerprint of Citrus Huanglongbing

https://abe.ufl.edu/precag/pdf/2015HLBDetectionAlireza1.pdf

An optimum method for real-time in-field detection of Huanglongbing disease using a vision sensor

Citrus greening detection using visible spectrum imaging and C-SVC

http://www.imok.ufl.edu/hlb/database/pdf/00002876.pdf

Laser-induced fluorescence imaging method to monitor citrus greening disease

http://www.imok.ufl.edu/hlb/database/pdf/00002896.pdf

Infrared spectroscopy: A potential tool in huanglongbing and citrus variegated chlorosis diagnosis

https://swfrec.ifas.ufl.edu/hlb/database/pdf/14_Ranulfi_16.pdf

Marcelo Camponez do Brasil Cardinali

Papers

Laser-induced fluorescence imaging method to monitor citrus greening disease

Infrared spectroscopy: A potential tool in huanglongbing and citrus variegated chlorosis diagnosis

Laser-induced fluorescence spectroscopy applied to early diagnosis of citrus Huanglongbing